Researchers developed a programmable plasmonic ring biosensor, MetaRing, to rapidly identify paclitaxel sensitivity in breast cancer patients. The platform achieved deterministic nanoparticle assembly and surface-enhanced Raman spectroscopy for rapid molecular analysis.
Researchers propose a universal mechanism for deterministic electrical control of collinear antiferromagnets, overcoming a long-standing bottleneck in antiferromagnetic spintronics. Asymmetric spin torque enables reliable flip of the Néel vector, making controlled data writing possible.
A new Metal–Organic Framework (MOF)-based material efficiently removes fluoride ions from water while providing real-time visual detection. This breakthrough overcomes limitations of conventional methods by integrating removal and monitoring processes.
An antiferromagnetic kagome semimetal heterostructure exhibits unconventional, damped oscillatory magnetoresistance in low-field regimes. Real-space magnetic force microscopy reveals topological magnetic textures that directly correlate with anomalous transport behavior.
Researchers successfully generated electrically controllable magnetic hopfions in a chiral magnet, representing a significant advancement in topological soliton research. The team's findings also revealed that the hopfions exhibit unconventional dynamics and transport behavior linked to their three-dimensional topology.
Researchers developed a fast, multi-platform compatible detection network that can detect gas leaks in three dimensions. The system achieves real-time detection at over 25 frames per second and provides accurate 3D reconstruction within 200 milliseconds.
Gradient-engineered cathode materials exhibit improved cycling stability and rate performance, demonstrating high capacity and strong long-term durability. The composition gradient strategy precisely regulates internal stress distribution and electronic structure, suppressing undesirable oxygen-related side reactions.
A research team from Hefei Institutes of Physical Science grew a high-entropy garnet-structured oxide crystal, achieving enhanced laser performance at 2.8 μm. The material demonstrated strong potential as a gain medium for mid-infrared ultrashort-pulse lasers.
Researchers provide new insights into how uncertainty propagation affects tokamak equilibrium reconstruction. They found reliable reconstruction requires controlled accuracy range for core diagnostic inputs and improved precision in midplane data.
Researchers discovered that magnetotactic bacteria can resist and detoxify lead, a highly toxic heavy metal pollutant. The bacteria use different strategies to handle lead, including adsorption on cell surfaces or absorption into cells.
A research team developed a novel amino-nitrogen–guided pore-engineering strategy to enhance sodium-ion transport and relieve interlayer confinement in hard carbon anodes. The process enables high initial efficiency, strong reversible capacity, and long-term cycling stability even under extreme conditions.
A team of researchers has discovered a high-energy-density barocaloric effect in Ag₂Te₁₋ₓSₓ, a plastic superionic conductor. The material produces a reversible volumetric entropy change of 0.478 J·cm⁻³·K⁻¹ under moderate pressure, surpassing most known inorganic materials.
Researchers developed a new deep learning method that boosts microplastic classification accuracy using the attention mechanism, outperforming traditional algorithms. The method achieves a classification accuracy of up to 98%, optimizing the model's performance and extracting more spectral features.
Researchers developed a novel immobilization strategy for surface plasmon resonance (SPR) assays of membrane proteins, effectively addressing technical constraints. The approach allows stable and specific capture of membrane proteins on sensor chips, enabling precise quantification of binding kinetics.
Researchers have discovered a single organic molecule can induce the Kondo effect, challenging long-held beliefs that it requires vast metallic electrons. The cobalt phthalocyanine molecule creates a 'molecular Kondo box' by hybridizing with conduction electrons of an underlying metal substrate.
Researchers at Hefei Institutes of Physical Science developed an ultra-compact excimer laser, eliminating mechanical gas pumps and reducing system volume. The laser achieved outstanding energy stability with a pulse energy exceeding 2 mJ while maintaining energy stability.
A new deep learning model, DSTMA-BLSTM, significantly enhances roadside air pollutant forecasting accuracy by 30% compared to conventional LSTM models. It achieves R² values exceeding 0.94 across major pollutants and demonstrates stable performance under complex traffic-meteorological coupling conditions.
A new method enhances precision and reliability of trace gas analysis in open-path infrared spectroscopic remote sensing. The integrated retrieval method combines VDL-DTCWT with NLLS fitting, significantly reducing background interference and improving pollutant concentration retrieval accuracy.
A research team at Hefei Institutes of Physical Science discovered a new mechanism for abnormal voltage attenuation in P2-type layered oxide cathodes. The study found that accumulation of unreduced molecular O2 leads to structural degradation and performance loss, highlighting the importance of bulk modification strategies.
A study improves marine aerosol remote sensing accuracy using multiangular polarimetry, which increases the degrees of freedom for signal (DFS) by at least 1.02 with added shortwave infrared measurements. This leads to the retrieval of one to two additional aerosol parameters and enhances understanding of columnar volume concentration,...
A team developed a bioinspired prussian blue/PNIPAM nanohybrid with spatiotemporally decoupled release characteristics, combining rapid and sustained release modes. The PAPP nanopesticides exhibited strong insecticidal activity while reducing harm to crops and non-target organisms.
Researchers developed a novel two-step plasma strategy to create surface-functionalized silver/mesoporous silica composites with strong antibacterial activity and positive surface charge. The modified materials showed improved interaction with bacterial membranes and effective suppression of E. coli infections.
Researchers developed an innovative approach to create dense dislocations in brittle superconductors, leading to a five-fold increase in critical current density. The technique utilizes asymmetric stress fields and scalable extrusion technology to induce localized lattice slip and twisting.
Researchers developed a novel robotic joint for heavy-duty robotics, achieving an ultra-high reduction ratio and delivering torque with low backlash. A deep reinforcement learning-based method also solved the problem of precise peg-in-hole assembly in radiation environments.
Researchers successfully engineered liquid-liquid phase separation-driven membraneless organelles (MLOs) in Corynebacterium glutamicum, resulting in a 2.43-fold increase in indigoidine titer. The technology enables spatial isolation of antimicrobial peptides, reducing toxicity and enabling successful expression.
Researchers developed an integrated method to accurately measure hemoglobin levels using near-infrared spectroscopy, overcoming limitations caused by strong water absorption and sample scattering. The approach significantly reduced background noise and achieved high accuracy, making it a reliable tool for non-invasive blood analysis.
Researchers developed a high-symmetry gradient-doped Nd:YAG laser crystal that reduces temperature differences between the center and ends, resulting in higher output power and improved beam quality. The crystal showed a 14 W output with efficiency boosted by more than half, making it suitable for dual-end pumping configurations.
A research team has discovered VOCs that can serve as reliable markers for multi-cancer screening. Early tumor signals were detectable in urine at week 5, in odor at week 13, and in feces at week 17.
A two-year field experiment found that one-time nitrogen application increases both soil and canopy ammonia emissions in maize fields. Split nitrogen application is a more sustainable choice with lower NH3 emissions and better maize productivity.
A team of researchers developed a self-sustaining solar-powered system that produces green hydrogen by coupling photothermal atmospheric water harvesting with proton exchange membrane electrolysis. The system maintains stable performance even under low humidity conditions, reaching a hydrogen production rate of nearly 300 mL per hour.
A team developed a method using generative adversarial networks (GANs) to learn underlying patterns in real spectrograms and reconstruct species-specific vocal components. This approach captures hidden features of the acoustic space, enabling precise separation of target sound sources and effective removal of environmental noise.
Researchers develop natural electron donor–assisted healing and targeted surface reconstruction strategy to regenerate degraded LiFePO₄ cathode materials. The approach reduces harmful defects and improves the rate performance of revived cathodes.
A new method for semi-supervised medical image segmentation outperforms traditional approaches by learning unified boundary feature representations across labeled and unlabeled data. The approach achieves competitive performance on benchmark datasets with as little as 10% labeled data.
A novel deep learning framework, CTCAIT, has been developed to detect early symptoms of Parkinson's, Huntington's, and Wilson disease through speech analysis. The model achieved a detection accuracy of 92.06% on a Mandarin Chinese dataset, demonstrating strong cross-linguistic generalizability.
A novel wearable eye patch using fluorescence sensors detects lysozyme levels in tears for early eye disease detection. The sensor's sensitivity is high enough to monitor lysozyme at concentrations as low as 1.5 nanomolar.
Researchers developed AI systems to enhance fusion energy experiments, predicting disruptions and monitoring plasma states with high accuracy. The tools improved reactor safety by 94% and achieved a 96.7% success rate in recognizing plasma conditions.
Researchers have discovered a new class of X-type antiferromagnetic materials that exhibit sublattice-selective spin transport and unconventional magnetic dynamics. This breakthrough enables precise control of the Néel vector, a crucial operation for antiferromagnetic spintronic data writing.
Researchers developed a high mechanical durability hydrogel electrolyte using urea as a zincophilic solubilizer, allowing for stable Zn stripping/plating in a dendrite and passivation-free manner. The material enhances the battery's overall performance and retention over time.
Researchers have proposed a third prototype of antiferromagnetic tunnel junction, paving the way for faster and denser spintronic devices. The new design, which relies on interface effects rather than bulk properties, allows for strong spin polarization and high performance.
A multi-omics study identified a key RNA-driven network behind colorectal cancer progression and immune resistance. Restoring a specific long non-coding RNA (lncRNA) expression reactivated tumor suppressor genes and enhanced immune cell infiltration, promoting anti-tumor effects.
Researchers developed a novel electroenzymatic platform enabling efficient non-natural oxidation reactions with high enantiomeric excess, opening a new chapter in biocatalysis for asymmetric synthesis
IHMT-15130, a selective BMX inhibitor, demonstrates robust efficacy in preclinical models of cardiac hypertrophy by suppressing inflammation and reversing pathological heart muscle thickening. The compound offers a safer therapeutic window for treating this major cardiovascular disorder.
Researchers developed a novel model optimization algorithm named External Calibration-Assisted Screening (ECA) to enhance the prediction robustness of Near-Infrared Spectroscopy (NIRS) quantitative models. ECA rapidly adapts initial models to new detection environments by calibrating them with externally collected samples.
Researchers found that 7-tesla magnetic fields accelerate demagnetization by 60% while suppressing efficiency by 34%, enabling widespread ultrafast demagnetization in other materials. Elevated temperatures enhance regulatory effects, promising real-world applications in high-speed storage and logic devices.
Researchers developed novel PbWO4 filler-reinforced B4C/HDPE composites with tunable microstructures, achieving enhanced synergistic radiation shielding performance. The optimized composite achieved a 97.32% shielding rate against ²⁵²Cf neutrons and 76.43% against ¹³⁷Cs gamma photons.
A recent study has shown that large language models (LLMs) can accurately predict liver cancer treatment responses, offering a new path towards AI-powered precision medicine. The LLMs demonstrated predictive accuracy on par with senior doctors, while outperforming junior and mid-level clinicians in speed and accuracy.
Researchers have engineered high-affinity antibodies against malaria by incorporating domains from inhibitory receptors, allowing them to block the interaction between parasite proteins and host immune cells. This new strategy offers a promising approach for treating malaria and could lead to innovative antimalarial drug discovery.
A compact all-solid-state CW SLM laser with high frequency stability was developed using iodine-based frequency locking, advancing its application in atmospheric remote sensing and environmental monitoring. The laser achieves long-term frequency stability with a drift of 4 MHz over a continuous 7-hour period.
A new AI-powered model has been developed to predict surface ozone concentration in the North China Plain and Yangtze River Delta regions. The model achieves high prediction accuracy, with hit rates of 83% and R² ≥ 0.85, providing a clearer picture of how weather patterns drive ozone pollution.
A new AI-powered model, PCWS, accurately predicts lung motion with a mean prediction error of just 0.20 mm, eliminating the need for 4D imaging. This approach represents a promising step toward personalized, low-risk treatment planning in lung cancer care.